NEMO ocean model P. A. Perezhogin. INM RAS CITES 2019 Motivation - - PowerPoint PPT Presentation

β–Ά
nemo ocean model
SMART_READER_LITE
LIVE PREVIEW

NEMO ocean model P. A. Perezhogin. INM RAS CITES 2019 Motivation - - PowerPoint PPT Presentation

Aug 28, 2022 17 likes β€’217 views

Backscatter parameterizations in NEMO ocean model P. A. Perezhogin. INM RAS CITES 2019 Motivation Mesoscale eddies are badly resolved in climate ocean models Consequently, eddy activity is damped It leads to wrong eddy fluxes and

slide-1
SLIDE 1

Backscatter parameterizations in NEMO ocean model

  • P. A. Perezhogin. INM RAS

CITES 2019

slide-2
SLIDE 2

Motivation

  • Mesoscale eddies are badly resolved in

climate ocean models

  • Consequently, eddy activity is damped
  • It leads to wrong eddy fluxes and mean state
  • Eddy activity can be amplified using

backscatter parameterizations

slide-3
SLIDE 3

Kinetic energy backscatter (KEB)

  • KEB is a process of energy flux from unresolved to resolved

turbulence motions

  • KEB is opposite to turbulent viscosity
  • KEB can be estimated using high resolution model
  • Contrary to 3D turbulence, in 2D backscatter is much stronger

due to the inverse direction of energy cascade

  • Energetically consistent backscatter is calibrated together with

turbulent viscosity based on the fact: in 2D turbulence total energy exchange of unresolved and resolved scales is zero

slide-4
SLIDE 4

Double Gyre configuration of NEMO primitive equation model

π‘’π‘ˆ 𝑒𝑒 = 0, 𝑒𝑇 𝑒𝑒 = 0 πœ–π‘½β„Ž πœ–π‘’ + π›πžπ’˜β„Ž + ππ©π’”β„Ž = βˆ’ 1 𝜍0 π›Όβ„Žπ‘ž πœ–π‘ž πœ–π‘¨ = βˆ’πœπ‘• 𝛼 β‹… 𝑽 = 0 πœ–πœƒ πœ–π‘’ = βˆ’π›Όβ„Ž β‹… 𝐼 + πœƒ π‘½β„Ž 𝜍 = 𝜍0(1 βˆ’ 𝑏 π‘ˆ βˆ’ π‘ˆ0 + 𝑐(𝑇 βˆ’ 𝑇0))

π‘ˆ, 𝑇, 𝑽, π‘½β„Ž, π‘½β„Ž, π‘ž, πœƒ, 𝜍, 𝐼 – potential temperature; salinity; velocity; horizontal velocity; vertically-averaged horizontal velocity; pressure; surface elevation; density; depth.

slide-5
SLIDE 5

Double Gyre parameters

  • 3180 𝑙𝑛 Γ— 2120 𝑙𝑛 Γ— 4𝑙𝑛
  • Box is rotated 45𝑝 to zonal direction
  • Beta-plane approximation
  • Free-slip boundaries, quadratic bottom drag
  • Surface forcings:
  • Zonal wind
  • Atmospheric heat flux
  • Fresh water flux
  • Solar radiation
slide-6
SLIDE 6

Model spin-up

R1 R1 R4 R4 R9 R9

π‘œπ‘¦ Γ— π‘œπ‘§ Γ— π‘œπ‘¨ 30 Γ— 20 Γ— 30 120 Γ— 80 Γ— 30 270 Γ— 180 Γ— 30

mesh step

10, 106 𝑙𝑛 1/40, 26.5 𝑙𝑛 1/90, 11.7 𝑙𝑛

Non-eddy-resolving Eddy-permitting Eddy-resolving

  • 1000 years R1 model
  • Then 100 years R4 and R9
slide-7
SLIDE 7

Relative vorticity snapshots at different resolutions

1/27𝑝 1/9𝑝 1/4𝑝 1𝑝

slide-8
SLIDE 8

Vorticity Temperature

slide-9
SLIDE 9

Meridional heat flux, R9

Eddy flux Mean flux Full flux

Eddy flux in depth

slide-10
SLIDE 10

R9 eddy flux R4 eddy flux

slide-11
SLIDE 11

Eddy heat flux models Viscosity reduction in R4

Viscosity reduction

slide-12
SLIDE 12

Negative viscosity backscatter (Jansen 2015)

πœ–π‘½β„Ž πœ–π‘’ = β‹― + πœ‰4Ξ”β„Ž

2π‘½β„Ž + π›Όβ„Ž πœ‰2π›Όβ„Žπ‘½β„Ž

πœ‰2 = βˆ’Ξ”π‘¦ β‹… 𝑑𝑐𝑏𝑑𝑙 max(𝑓, 0) 𝑒𝑓 𝑒𝑒 = ሢ 𝐹𝑒𝑗𝑑𝑑 + ሢ 𝐹𝑐𝑏𝑑𝑙 + πœ‰π‘“Ξ”π‘“

πœ‰4 = π‘‘π‘π‘œπ‘‘π‘’ < 0, πœ‰2 ≀ 0 ሢ 𝐹𝑒𝑗𝑑𝑑 = πœ‰4π›Όβ„Žπ‘½β„Ž β‹… π›Όβ„Ž(Ξ”β„Žπ‘½β„Ž) ሢ 𝐹𝑐𝑏𝑑𝑙 = πœ‰2π›Όβ„Žπ‘½β„Ž β‹… π›Όβ„Žπ‘½β„Ž

  • β€œEnergetically consistent” – zero energy exchange with unresolved scales
  • Energy returning using Laplace operator with negative viscosity
  • Viscosity varies in space and time πœ‰2 𝑦, 𝑧, 𝑨, 𝑒
  • Additional equation for subgrid energy 𝑓(𝑦, 𝑧, 𝑨, 𝑒)
slide-13
SLIDE 13

Stochastic backscatter (Grooms, Majda2017; Berner2009)

  • πœ” 𝑦, 𝑧, 𝑨 = 𝜚 𝑦, 𝑧 β‹…

max ሢ 𝐹𝑒𝑗𝑑𝑑, 0

  • 𝜚(𝑦, 𝑧) – white noise in space and time, 𝑂(0,1)

πœ–π‘‰β„Ž πœ–π‘’ = β‹― + 𝛽𝛼βŠ₯ ΰ·  πœ”, Where ΰ·’ (β‹…) - 6 applications of Laplace filter nullifying chess-noise

  • Condition on amplitude 𝛽 representing global energy balance:

𝛽2Δ𝑒 2 ΰΆ± 𝛼βŠ₯ ΰ·  πœ”

2π‘’π‘Š = ΰΆ± ሢ

𝐹𝑒𝑗𝑑𝑑 π‘’π‘Š

slide-14
SLIDE 14

Eddy kinetic energy (EKE) in colour, SST in contours

slide-15
SLIDE 15

Eddy heat flux in colour, MOC in contours

Ψ𝑁𝑃𝐷 𝑧, 𝑨 = ΰΆ±

βˆ’πΌ βˆ’π‘¨

ΰΆ± π‘Š(𝑦, 𝑧, 𝑨)𝑒𝑦𝑒𝑨′

slide-16
SLIDE 16

Time spectra averaged

  • ver the black rectangle
slide-17
SLIDE 17

Errors in mean state max πœšπ‘†4 βˆ’ πœšπ‘†9 and mean πœšπ‘†4 βˆ’ πœšπ‘†9

R4 R4 negative viscosity R4 stochastic SST, 𝐷𝑝 7.04 0.37 3.00 0.28 4.33 0.27 SSH, m 0.707 0.063 0.378 0.038 0.419 0.040

slide-18
SLIDE 18

The main drawback – maximum energy exchange near the boundary

slide-19
SLIDE 19

Conclusions

  • Backscatter can amplify mesoscale eddies
  • Improvements are seen in mean fields (SST, SSH, MOC), in

variability (EKE, time spectra) and in cross-correlation (eddy heat flux)

  • Stochastic and negative viscosity KEBs are qualitatively similar
slide-20
SLIDE 20

Relative vorticity snapshots at different resolutions

1/27𝑝 1/9𝑝 1/4𝑝 1𝑝 1/4𝑝 + neg.visc